Abstract
BACKGROUND: Excess nitrogen (N) loading to coastal ecosystems impairs estuarine water quality. Land management decisions made within estuarine watersheds have a direct impact on downstream N delivery. Natural features within watersheds can act as landscape sinks for N, such as wetlands, streams and ponds that transform dissolved N into gaseous N, effectively removing it from the aquatic system. Identifying and evaluating these landscape sinks and their spatial relationship to N sources can help managers understand the effects of alternative decisions on downstream resources. METHODS: The N-Sink approach uses widely available GIS data to identify landscape sinks within HUC-12 (or larger) catchments, estimate their N removal potential and map the effect of those sinks on N movement through the catchment. Static maps are produced to visualize N removal efficiency, transport and delivery, the latter in the form of an index. The R package nsink was developed to facilitate data acquisition, processing and visualization. RESULTS: nsink creates static maps for a specific HUC-12, or users can visit the University of Connecticut website to explore previously mapped areas. Users can investigate specific flowpaths interactively by clicking on any location within the catchment. A flowpath is generated with a table describing N removal along each segment. We describe the motivation behind developing nsink, discuss implementation in R, and present two use case examples. nsink is available from https://github.com/USEPA/nsink. CONCLUSIONS: N-Sink is a decision support tool created for local decision-makers and NGOs to facilitate better understanding of the relationship between land use and downstream N delivery. Local decision-makers that have prioritized N mitigation in their long-term planning can use nsink to better understand the potential impact of proposed development projects, zoning variances, and land acquisition or restoration. nsink also allows resource economists to investigate the tradeoffs among different, often costly, N reduction strategies.